Constrained 2D Sketch Generation Based on Image Contour Detect

Local description and retrieval method for binary image contour

Journal of Computer Applications ◽

10.3724/sp.j.1087.2010.00065 ◽

2010 ◽

Vol 30 (1) ◽

pp. 65-67 ◽

Cited By ~ 2

Author(s):

Xiao-dong YANG ◽

Ling-da WU ◽

Yu-xiang XIE ◽

Zheng YANG ◽

Wen ZHOU

Keyword(s):

Binary Image ◽

Retrieval Method ◽

Local Description ◽

Image Contour

Download Full-text

Underwater Image Enhancement Method Combining color and Luminance

Recent Advances in Electrical & Electronic Engineering (Formerly Recent Patents on Electrical & Electronic Engineering) ◽

10.2174/2352096513999201026225829 ◽

2020 ◽

Vol 13 ◽

Author(s):

ZHAO Baiting ◽

WANG Feng ◽

JIA Xiaofen ◽

GUO Yongcun ◽

WANG Chengjun

Keyword(s):

Image Enhancement ◽

Color Space ◽

Low Frequency ◽

Brightness Enhancement ◽

Color Distortion ◽

Underwater Image ◽

Enhancement Method ◽

Frequency Components ◽

Image Contour ◽

Objective Indicators

Background:: Aiming at the problems of color distortion, low clarity and poor visibility of underwater image caused by complex underwater environment, a wavelet fusion method UIPWF for underwater image enhancement is proposed. Methods:: First of all, an improved NCB color balance method is designed to identify and cut the abnormal pixels, and balance the color of R, G and B channels by affine transformation. Then, the color correction map is converted to CIELab color space, and the L component is equalized with contrast limited adaptive histogram to obtain the brightness enhancement map. Finally, different fusion rules are designed for low-frequency and high-frequency components, the pixel level wavelet fusion of color balance image and brightness enhancement image is realized to improve the edge detail contrast on the basis of protecting the underwater image contour. Results:: The experiments demonstrate that compared with the existing underwater image processing methods, UIPWF is highly effective in the underwater image enhancement task, improves the objective indicators greatly, and produces visually pleasing enhancement images with clear edges and reasonable color information. Conclusion:: The UIPWF method can effectively mitigate the color distortion, improve the clarity and contrast, which is applicable for underwater image enhancement in different environments.

Download Full-text

Realization of clothing image contour extraction and collar segmentation

Journal of Physics Conference Series ◽

10.1088/1742-6596/1790/1/012091 ◽

2021 ◽

Vol 1790 (1) ◽

pp. 012091

Author(s):

Ling Zhang ◽

Zengbo Xu ◽

Yanhong Zhang

Keyword(s):

Contour Extraction ◽

Image Contour

Download Full-text

Algorithm for recognition of details in the machine vision systems at automation of assembly processes

MATEC Web of Conferences ◽

10.1051/matecconf/201822401088 ◽

2018 ◽

Vol 224 ◽

pp. 01088 ◽

Cited By ~ 1

Author(s):

Yaroslav Kulkov ◽

Arkady Zhiznyakov ◽

Denis Privezentsev

Keyword(s):

Computer Vision ◽

Experimental Research ◽

Mean Square ◽

Robot Arm ◽

Vision Systems ◽

Binary Images ◽

Image Contour ◽

Computer Vision Systems ◽

Assembly Operations ◽

Unknown Object

The aim is an experimental research on the flat objects recognition using dimensionless marks of the contours of their binary images and determining the possibility of applying this method in computer vision systems of assembly robots. The main problem with the automation of assembly operations is the recognition of parts for the subsequent picking up of the robot arm. The basis for the formation of attribute vectors is the characteristics of the image contour. Recognition of a class of an unknown object consists in receipt of its contour, calculation of primary parameters and forming of a vector of dimensionless marks. Further mean square deviations of its vector of dimensionless marks from all reference are calculated. The minimum value of a deviation will specify probable belonging to the corresponding class.

Download Full-text